Traffic hotspot localization in 3G and 4G wireless networks using OMC metrics

2016 IEEE International Conference on Communications (ICC)

Nasri²,

Chahed³

2016

Self Cite

Abstract-In this paper, the concept of moving small cells in mobile networks is presented and evaluated taking into account the dynamics of the system. We consider a small cell moving according to a Manhattan mobility model which is the case when the small cell is deployed on the top of a bus following a predefined trajectory in areas which are generally crowded. Taking into account the distribution of user locations, we study the dynamic level considering a queuing model composed of multi-class Processor Sharing queues. Macro and small cells are assumed to be operating in the same bandwidth. Consequently, they are coupled due to the mutual interferences generated by each cell to the other. Our results show that deploying moving small cells could be an efficient solution to offload traffic hotspots.

Section: A Moving Small Cells Concept and Evolutionmentioning

confidence: 99%

Offloading traffic hotspots using moving small cells

2016 IEEE International Conference on Communications (ICC)

Nasri²,

Chahed³

2016

Self Cite

“…In fact, for a traffic HS in 520m far from the MC, the SC still improve the mean user throughput in the MC even with an error of HS localization of 160m which is not the case for a HS in 350m far from the MC. In such scenarios, some traffic HS localization techniques [12], [13] can be implemented and used in operational SC planning tools. Results in Fig.…”

Section: Numerical Resultsmentioning

confidence: 99%

Performance Analysis of Small Cells' Deployment under Imperfect Traffic Hotspot Localization

2015 IEEE Global Communications Conference (GLOBECOM)

Nasri

Chahed³

2015

Self Cite

Abstract-Heterogeneous Networks (HetNets), long been considered in operators' roadmaps for macrocells' network improvements, still continue to attract interest for 5G network deployments. Understanding the efficiency of small cell deployment in the presence of traffic hotspots can further draw operators' attention to this feature. In this context, we evaluate the impact of imperfect small cell positioning on the network performances. We show that the latter is mainly impacted by the position of the hotspot within the cell: in case the hotspot is near the macrocell, even a perfect positioning of the small cell will not yield improved performance due to the interference coming from the macrocell. In the case where the hotspot is located far enough from the macrocell, even a large error in small cell positioning would still be beneficial in offloading traffic from the congested macrocell.

“…All the provided expressions of the ISR are valid for a propagation parameter b > 1. The second contribution of this work is the explicit derivation of the network performances in terms of SINR distribution in hexagonal networks with an arbitrary user locations' distribution reflecting the spatial traffic density [20]. The finding of SINR distribution entails of course the inversion of the SINR, taken as a function of location m. To show the utility of the explicit formula of the SINR distribution, we numerically investigate the SINR distribution for two scenarios of user locations: uniform and heavy-tailed distributions (e.g., Lognormal user location distribution).…”

Section: Contributionsmentioning

confidence: 99%

Analytical Tractability of Hexagonal Network Model With Random User Location

Nasri

IEEE Trans. Wireless Commun.

2016

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Abstract-Explicit derivation of interferences in hexagonal wireless networks has been widely considered intractable and requires extensive computations with system level simulations. In this paper, we fundamentally tackle this problem and explicitly evaluate the downlink Interference-to-Signal Ratio (ISR) for any mobile location m in a hexagonal wireless network, whether composed of omni-directional or tri-sectorized sites. The explicit formula of ISR is a very convergent series on m and involves the use of Gauss hypergeometric and Hurwitz Riemann zeta functions. Besides, we establish simple identities that well approximate this convergent series and turn out quite useful compared to other approximations in literature. The derived expression of ISR is easily extended to any frequency reuse pattern. Moreover, it is also exploited in the derivation of an explicit form of SINR distribution for any arbitrary distribution of mobile user locations, reflecting the spatial traffic density in the network. Knowing explicitly about interferences and SINR distribution is very useful information in capacity and coverage planning of wireless cellular networks and particularly for macrocells' layer that forms almost a regular point pattern.